{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1 对Capital Bikeshare数据进行探索分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据读取及基本处理\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# plotting\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# setting params\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (30, 10),\n",
    "          'axes.labelsize': 'x-large',\n",
    "          'axes.titlesize':'x-large',\n",
    "          'xtick.labelsize':'x-large',\n",
    "          'ytick.labelsize':'x-large'}\n",
    "\n",
    "sn.set_style('whitegrid')\n",
    "sn.set_context('talk')\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "pd.options.display.max_colwidth = 600\n",
    "\n",
    "# pandas display data frames as tables\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读入数据\n",
    "train = pd.read_csv(\"day.csv\")\n",
    "train.head()\n",
    "#print(\"train : \" + str(train.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对数据值型特征，用常用统计量观察其分布\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "season属性的不同取值和出现的次数\n",
      "3    188\n",
      "2    184\n",
      "1    181\n",
      "4    178\n",
      "Name: season, dtype: int64\n",
      "\n",
      "mnth属性的不同取值和出现的次数\n",
      "12    62\n",
      "10    62\n",
      "8     62\n",
      "7     62\n",
      "5     62\n",
      "3     62\n",
      "1     62\n",
      "11    60\n",
      "9     60\n",
      "6     60\n",
      "4     60\n",
      "2     57\n",
      "Name: mnth, dtype: int64\n",
      "\n",
      "weathersit属性的不同取值和出现的次数\n",
      "1    463\n",
      "2    247\n",
      "3     21\n",
      "Name: weathersit, dtype: int64\n",
      "\n",
      "weekday属性的不同取值和出现的次数\n",
      "6    105\n",
      "1    105\n",
      "0    105\n",
      "5    104\n",
      "4    104\n",
      "3    104\n",
      "2    104\n",
      "Name: weekday, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#对类别型特征，观察其取值范围及直方图\n",
    "categorical_features = ['season','mnth','weathersit','weekday']\n",
    "for col in categorical_features:\n",
    "    print('\\n%s属性的不同取值和出现的次数'%col) \n",
    "    print(train[col].value_counts()) \n",
    "    train[col] = train[col].astype('object')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1 骑车量的年分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c493055ba8>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=train[['yr',\n",
    "                          'cnt']],\n",
    "              x=\"yr\",y=\"cnt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.2 骑车量的每天分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'dayly distribution of counts')]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import datetime\n",
    "\n",
    "train['date'] = pd.to_datetime(train['dteday'])\n",
    "train['dayofyear'] = train[\"date\"].dt.dayofyear  #减今年的第几天\n",
    "\n",
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=train[['dayofyear',\n",
    "                           'cnt',\n",
    "                           'yr']],\n",
    "             x='dayofyear',y='cnt',\n",
    "             hue='yr',ax=ax)\n",
    "ax.set(title=\"dayly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3 骑车量与季节的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'Seasonly distribution of counts')]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['season',\n",
    "                       'cnt']],\n",
    "           x=\"season\",y=\"cnt\")\n",
    "ax.set(title=\"Seasonly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.4 骑车量与月份的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'Monthly distribution of counts')]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['mnth',\n",
    "                       'cnt']],\n",
    "           x=\"mnth\",y=\"cnt\")\n",
    "ax.set(title=\"Monthly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.5 骑车量与天气的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'weathersit distribution of counts')]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[['weathersit',\n",
    "                       'cnt']],\n",
    "           x=\"weathersit\",y=\"cnt\")\n",
    "ax.set(title=\"weathersit distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.6 骑车量在工作日和节假日的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c4945b7e10>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(ncols=2)\n",
    "sn.barplot(data=train,x='holiday',y='cnt',hue='season',ax=ax1)\n",
    "sn.barplot(data=train,x='workingday',y='cnt',hue='season',ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.7 骑车量与各个特征量的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c4937e05f8>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrMatt = train[[\"temp\",\"atemp\",\n",
    "                  \"hum\",\"windspeed\",\n",
    "                  \"casual\",\"registered\",\n",
    "                  \"cnt\"]].corr()\n",
    "mask = np.array(corrMatt)\n",
    "mask[np.tril_indices_from(mask)] = False\n",
    "sn.heatmap(corrMatt, mask=mask,\n",
    "           vmax=.8, square=True,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season_1</th>\n",
       "      <th>season_2</th>\n",
       "      <th>season_3</th>\n",
       "      <th>season_4</th>\n",
       "      <th>mnth_1</th>\n",
       "      <th>mnth_2</th>\n",
       "      <th>mnth_3</th>\n",
       "      <th>mnth_4</th>\n",
       "      <th>mnth_5</th>\n",
       "      <th>mnth_6</th>\n",
       "      <th>...</th>\n",
       "      <th>weathersit_1</th>\n",
       "      <th>weathersit_2</th>\n",
       "      <th>weathersit_3</th>\n",
       "      <th>weekday_0</th>\n",
       "      <th>weekday_1</th>\n",
       "      <th>weekday_2</th>\n",
       "      <th>weekday_3</th>\n",
       "      <th>weekday_4</th>\n",
       "      <th>weekday_5</th>\n",
       "      <th>weekday_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   season_1  season_2  season_3  season_4  mnth_1  mnth_2  mnth_3  mnth_4  \\\n",
       "0         1         0         0         0       1       0       0       0   \n",
       "1         1         0         0         0       1       0       0       0   \n",
       "2         1         0         0         0       1       0       0       0   \n",
       "3         1         0         0         0       1       0       0       0   \n",
       "4         1         0         0         0       1       0       0       0   \n",
       "\n",
       "   mnth_5  mnth_6    ...      weathersit_1  weathersit_2  weathersit_3  \\\n",
       "0       0       0    ...                 0             1             0   \n",
       "1       0       0    ...                 0             1             0   \n",
       "2       0       0    ...                 1             0             0   \n",
       "3       0       0    ...                 1             0             0   \n",
       "4       0       0    ...                 1             0             0   \n",
       "\n",
       "   weekday_0  weekday_1  weekday_2  weekday_3  weekday_4  weekday_5  weekday_6  \n",
       "0          0          0          0          0          0          0          1  \n",
       "1          1          0          0          0          0          0          0  \n",
       "2          0          1          0          0          0          0          0  \n",
       "3          0          0          1          0          0          0          0  \n",
       "4          0          0          0          1          0          0          0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features = ['season','mnth','weathersit','weekday']\n",
    "x_train_cat = train[categorical_features]\n",
    "x_train_cat = pd.get_dummies(x_train_cat)\n",
    "x_train_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.379232</td>\n",
       "      <td>0.360541</td>\n",
       "      <td>0.715771</td>\n",
       "      <td>0.466215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.171000</td>\n",
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       "      <td>0.465740</td>\n",
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       "    <tr>\n",
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       "      <td>0.449313</td>\n",
       "      <td>0.339143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       temp     atemp       hum  windspeed\n",
       "0  0.355170  0.373517  0.828620   0.284606\n",
       "1  0.379232  0.360541  0.715771   0.466215\n",
       "2  0.171000  0.144830  0.449638   0.465740\n",
       "3  0.175530  0.174649  0.607131   0.284297\n",
       "4  0.209120  0.197158  0.449313   0.339143"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数值型变量预处理\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "mn_x = MinMaxScaler()\n",
    "numerical_features = ['temp','atemp','hum','windspeed']\n",
    "temp = mn_x.fit_transform(train[numerical_features])\n",
    "\n",
    "x_train_num = pd.DataFrame(data=temp, columns=numerical_features, index =train.index)\n",
    "x_train_num.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season_1</th>\n",
       "      <th>season_2</th>\n",
       "      <th>season_3</th>\n",
       "      <th>season_4</th>\n",
       "      <th>mnth_1</th>\n",
       "      <th>mnth_2</th>\n",
       "      <th>mnth_3</th>\n",
       "      <th>mnth_4</th>\n",
       "      <th>mnth_5</th>\n",
       "      <th>mnth_6</th>\n",
       "      <th>...</th>\n",
       "      <th>weekday_3</th>\n",
       "      <th>weekday_4</th>\n",
       "      <th>weekday_5</th>\n",
       "      <th>weekday_6</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.209120</td>\n",
       "      <td>0.197158</td>\n",
       "      <td>0.449313</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   season_1  season_2  season_3  season_4  mnth_1  mnth_2  mnth_3  mnth_4  \\\n",
       "0         1         0         0         0       1       0       0       0   \n",
       "1         1         0         0         0       1       0       0       0   \n",
       "2         1         0         0         0       1       0       0       0   \n",
       "3         1         0         0         0       1       0       0       0   \n",
       "4         1         0         0         0       1       0       0       0   \n",
       "\n",
       "   mnth_5  mnth_6     ...      weekday_3  weekday_4  weekday_5  weekday_6  \\\n",
       "0       0       0     ...              0          0          0          1   \n",
       "1       0       0     ...              0          0          0          0   \n",
       "2       0       0     ...              0          0          0          0   \n",
       "3       0       0     ...              0          0          0          0   \n",
       "4       0       0     ...              1          0          0          0   \n",
       "\n",
       "       temp     atemp       hum  windspeed  holiday  workingday  \n",
       "0  0.355170  0.373517  0.828620   0.284606        0           0  \n",
       "1  0.379232  0.360541  0.715771   0.466215        0           0  \n",
       "2  0.171000  0.144830  0.449638   0.465740        0           1  \n",
       "3  0.175530  0.174649  0.607131   0.284297        0           1  \n",
       "4  0.209120  0.197158  0.449313   0.339143        0           1  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Join categorical and numerical features\n",
    "x_train = pd.concat([x_train_cat, x_train_num, train['holiday'],  train['workingday']], axis = 1, ignore_index=False)\n",
    "x_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.144830</td>\n",
       "      <td>0.449638</td>\n",
       "      <td>0.465740</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.175530</td>\n",
       "      <td>0.174649</td>\n",
       "      <td>0.607131</td>\n",
       "      <td>0.284297</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.209120</td>\n",
       "      <td>0.197158</td>\n",
       "      <td>0.449313</td>\n",
       "      <td>0.339143</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant  season_1  season_2  season_3  season_4  mnth_1  mnth_2  mnth_3  \\\n",
       "0        1         1         0         0         0       1       0       0   \n",
       "1        2         1         0         0         0       1       0       0   \n",
       "2        3         1         0         0         0       1       0       0   \n",
       "3        4         1         0         0         0       1       0       0   \n",
       "4        5         1         0         0         0       1       0       0   \n",
       "\n",
       "   mnth_4  mnth_5  ...   weekday_5  weekday_6      temp     atemp       hum  \\\n",
       "0       0       0  ...           0          1  0.355170  0.373517  0.828620   \n",
       "1       0       0  ...           0          0  0.379232  0.360541  0.715771   \n",
       "2       0       0  ...           0          0  0.171000  0.144830  0.449638   \n",
       "3       0       0  ...           0          0  0.175530  0.174649  0.607131   \n",
       "4       0       0  ...           0          0  0.209120  0.197158  0.449313   \n",
       "\n",
       "   windspeed  holiday  workingday  yr   cnt  \n",
       "0   0.284606        0           0   0   985  \n",
       "1   0.466215        0           0   0   801  \n",
       "2   0.465740        0           1   0  1349  \n",
       "3   0.284297        0           1   0  1562  \n",
       "4   0.339143        0           1   0  1600  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FE_train = pd.concat([train['instant'], x_train,  train['yr'],train['cnt']], axis = 1)\n",
    "FE_train.to_csv('FE_day.csv', index=False)\n",
    "FE_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 35 columns):\n",
      "instant         731 non-null int64\n",
      "season_1        731 non-null uint8\n",
      "season_2        731 non-null uint8\n",
      "season_3        731 non-null uint8\n",
      "season_4        731 non-null uint8\n",
      "mnth_1          731 non-null uint8\n",
      "mnth_2          731 non-null uint8\n",
      "mnth_3          731 non-null uint8\n",
      "mnth_4          731 non-null uint8\n",
      "mnth_5          731 non-null uint8\n",
      "mnth_6          731 non-null uint8\n",
      "mnth_7          731 non-null uint8\n",
      "mnth_8          731 non-null uint8\n",
      "mnth_9          731 non-null uint8\n",
      "mnth_10         731 non-null uint8\n",
      "mnth_11         731 non-null uint8\n",
      "mnth_12         731 non-null uint8\n",
      "weathersit_1    731 non-null uint8\n",
      "weathersit_2    731 non-null uint8\n",
      "weathersit_3    731 non-null uint8\n",
      "weekday_0       731 non-null uint8\n",
      "weekday_1       731 non-null uint8\n",
      "weekday_2       731 non-null uint8\n",
      "weekday_3       731 non-null uint8\n",
      "weekday_4       731 non-null uint8\n",
      "weekday_5       731 non-null uint8\n",
      "weekday_6       731 non-null uint8\n",
      "temp            731 non-null float64\n",
      "atemp           731 non-null float64\n",
      "hum             731 non-null float64\n",
      "windspeed       731 non-null float64\n",
      "holiday         731 non-null int64\n",
      "workingday      731 non-null int64\n",
      "yr              731 non-null int64\n",
      "cnt             731 non-null int64\n",
      "dtypes: float64(4), int64(5), uint8(26)\n",
      "memory usage: 70.0 KB\n"
     ]
    }
   ],
   "source": [
    "FE_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1 将数据分割为80%的训练集和20%的校验集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从原始数据中分离输入特征x和输出y\n",
    "y = FE_train['cnt'].values\n",
    "X = FE_train.drop('cnt', axis = 1)\n",
    "\n",
    "#用于后续显示权重系数对应的特征\n",
    "columns = X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(584, 34)"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将数据分割训练数据与测试数据\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 随机采样20%的数据构建测试集，其余80%作为训练集\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=33, test_size=0.2)\n",
    "X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3 确定模型类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 最小二乘线性回归模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>yr</td>\n",
       "      <td>4550.708897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>temp</td>\n",
       "      <td>2654.792827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>1287.992360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>atemp</td>\n",
       "      <td>995.293778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>929.887649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>914.410909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>season_4</td>\n",
       "      <td>830.579518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>586.296405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>517.803038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>409.589079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>407.138803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>238.417312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>workingday</td>\n",
       "      <td>216.956549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>189.797216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>season_2</td>\n",
       "      <td>85.141889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>77.516263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>66.464787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>43.650546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>5.009200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>instant</td>\n",
       "      <td>-6.919060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-31.943212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>season_3</td>\n",
       "      <td>-130.807162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-191.612446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-202.493250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-203.137582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-263.761415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-485.714239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-541.439917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>season_1</td>\n",
       "      <td>-784.914245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-1174.845790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-1207.111892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1298.592138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>-1323.999988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-1486.521042</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns         coef\n",
       "33            yr  4550.708897\n",
       "27          temp  2654.792827\n",
       "13        mnth_9  1287.992360\n",
       "28         atemp   995.293778\n",
       "14       mnth_10   929.887649\n",
       "17  weathersit_1   914.410909\n",
       "4       season_4   830.579518\n",
       "16       mnth_12   586.296405\n",
       "12        mnth_8   517.803038\n",
       "18  weathersit_2   409.589079\n",
       "15       mnth_11   407.138803\n",
       "26     weekday_6   238.417312\n",
       "32    workingday   216.956549\n",
       "10        mnth_6   189.797216\n",
       "2       season_2    85.141889\n",
       "25     weekday_5    77.516263\n",
       "23     weekday_3    66.464787\n",
       "24     weekday_4    43.650546\n",
       "9         mnth_5     5.009200\n",
       "0        instant    -6.919060\n",
       "22     weekday_2   -31.943212\n",
       "3       season_3  -130.807162\n",
       "20     weekday_0  -191.612446\n",
       "21     weekday_1  -202.493250\n",
       "11        mnth_7  -203.137582\n",
       "31       holiday  -263.761415\n",
       "8         mnth_4  -485.714239\n",
       "7         mnth_3  -541.439917\n",
       "1       season_1  -784.914245\n",
       "30     windspeed -1174.845790\n",
       "6         mnth_2 -1207.111892\n",
       "29           hum -1298.592138\n",
       "19  weathersit_3 -1323.999988\n",
       "5         mnth_1 -1486.521042"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 线性回归\n",
    "#class sklearn.linear_model.LinearRegression(fit_intercept=True, normalize=False, copy_X=True, n_jobs=1)\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "# 使用默认配置初始化\n",
    "lr = LinearRegression()\n",
    "\n",
    "# 训练模型参数\n",
    "lr.fit(X_train, y_train)\n",
    "\n",
    "# 预测\n",
    "y_test_pred_lr = lr.predict(X_test)\n",
    "y_train_pred_lr = lr.predict(X_train)\n",
    "\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef\":list((lr.coef_.T))})\n",
    "fs.sort_values(by=['coef'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1.1 利用评估指标RMSE评估模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The RMSE of LinearRegression on test is 814.4749076863649\n",
      "The RMSE of LinearRegression on train is 742.7543512758713\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "# 测试集\n",
    "print('The RMSE of LinearRegression on test is', np.sqrt(metrics.mean_squared_error(y_test, y_test_pred_lr))) \n",
    "# 训练集\n",
    "print('The RMSE of LinearRegression on train is', np.sqrt(metrics.mean_squared_error(y_train, y_train_pred_lr))) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 岭回归模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>yr</td>\n",
       "      <td>4550.708897</td>\n",
       "      <td>1504.623924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>temp</td>\n",
       "      <td>2654.792827</td>\n",
       "      <td>1778.493414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>1287.992360</td>\n",
       "      <td>678.352931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>atemp</td>\n",
       "      <td>995.293778</td>\n",
       "      <td>1546.374034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>929.887649</td>\n",
       "      <td>84.873020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>914.410909</td>\n",
       "      <td>914.843092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>season_4</td>\n",
       "      <td>830.579518</td>\n",
       "      <td>767.205317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>586.296405</td>\n",
       "      <td>-824.928596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>517.803038</td>\n",
       "      <td>205.686009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>409.589079</td>\n",
       "      <td>388.865215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>407.138803</td>\n",
       "      <td>-725.828529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>238.417312</td>\n",
       "      <td>227.515740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>workingday</td>\n",
       "      <td>216.956549</td>\n",
       "      <td>212.558710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>189.797216</td>\n",
       "      <td>369.663154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>season_2</td>\n",
       "      <td>85.141889</td>\n",
       "      <td>110.998614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>77.516263</td>\n",
       "      <td>81.396550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>66.464787</td>\n",
       "      <td>59.857933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>43.650546</td>\n",
       "      <td>62.795850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>5.009200</td>\n",
       "      <td>387.713628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>instant</td>\n",
       "      <td>-6.919060</td>\n",
       "      <td>1.417157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-31.943212</td>\n",
       "      <td>-34.140080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>season_3</td>\n",
       "      <td>-130.807162</td>\n",
       "      <td>-91.388275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-191.612446</td>\n",
       "      <td>-191.851510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-202.493250</td>\n",
       "      <td>-205.574484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-203.137582</td>\n",
       "      <td>-242.548582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-263.761415</td>\n",
       "      <td>-248.222941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-485.714239</td>\n",
       "      <td>106.306513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-541.439917</td>\n",
       "      <td>298.550050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>season_1</td>\n",
       "      <td>-784.914245</td>\n",
       "      <td>-786.815656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-1174.845790</td>\n",
       "      <td>-1087.773198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-1207.111892</td>\n",
       "      <td>-143.125249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1298.592138</td>\n",
       "      <td>-1142.397276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>-1323.999988</td>\n",
       "      <td>-1303.708307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-1486.521042</td>\n",
       "      <td>-194.714350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns      coef_lr   coef_ridge\n",
       "33            yr  4550.708897  1504.623924\n",
       "27          temp  2654.792827  1778.493414\n",
       "13        mnth_9  1287.992360   678.352931\n",
       "28         atemp   995.293778  1546.374034\n",
       "14       mnth_10   929.887649    84.873020\n",
       "17  weathersit_1   914.410909   914.843092\n",
       "4       season_4   830.579518   767.205317\n",
       "16       mnth_12   586.296405  -824.928596\n",
       "12        mnth_8   517.803038   205.686009\n",
       "18  weathersit_2   409.589079   388.865215\n",
       "15       mnth_11   407.138803  -725.828529\n",
       "26     weekday_6   238.417312   227.515740\n",
       "32    workingday   216.956549   212.558710\n",
       "10        mnth_6   189.797216   369.663154\n",
       "2       season_2    85.141889   110.998614\n",
       "25     weekday_5    77.516263    81.396550\n",
       "23     weekday_3    66.464787    59.857933\n",
       "24     weekday_4    43.650546    62.795850\n",
       "9         mnth_5     5.009200   387.713628\n",
       "0        instant    -6.919060     1.417157\n",
       "22     weekday_2   -31.943212   -34.140080\n",
       "3       season_3  -130.807162   -91.388275\n",
       "20     weekday_0  -191.612446  -191.851510\n",
       "21     weekday_1  -202.493250  -205.574484\n",
       "11        mnth_7  -203.137582  -242.548582\n",
       "31       holiday  -263.761415  -248.222941\n",
       "8         mnth_4  -485.714239   106.306513\n",
       "7         mnth_3  -541.439917   298.550050\n",
       "1       season_1  -784.914245  -786.815656\n",
       "30     windspeed -1174.845790 -1087.773198\n",
       "6         mnth_2 -1207.111892  -143.125249\n",
       "29           hum -1298.592138 -1142.397276\n",
       "19  weathersit_3 -1323.999988 -1303.708307\n",
       "5         mnth_1 -1486.521042  -194.714350"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#岭回归／L2正则\n",
    "#class sklearn.linear_model.RidgeCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, \n",
    "#                                  normalize=False, scoring=None, cv=None, gcv_mode=None, \n",
    "#                                  store_cv_values=False)\n",
    "from sklearn.linear_model import  RidgeCV\n",
    "\n",
    "#设置超参数（正则参数）范围\n",
    "alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "#n_alphas = 20\n",
    "#alphas = np.logspace(-5,2,n_alphas)\n",
    "\n",
    "#生成一个RidgeCV实例\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "\n",
    "#模型训练\n",
    "ridge.fit(X_train, y_train)    \n",
    "\n",
    "#预测\n",
    "y_test_pred_ridge = ridge.predict(X_test)\n",
    "y_train_pred_ridge = ridge.predict(X_train)\n",
    "\n",
    "# 各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2.1 利用评估指标RMSE评估模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The RMSE of LinearRegression on test is 812.041268534034\n",
      "The RMSE of LinearRegression on train is 747.4410131599813\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "# 测试集\n",
    "print('The RMSE of LinearRegression on test is', np.sqrt(metrics.mean_squared_error(y_test, y_test_pred_ridge))) \n",
    "# 训练集\n",
    "print('The RMSE of LinearRegression on train is', np.sqrt(metrics.mean_squared_error(y_train, y_train_pred_ridge))) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2.2 5折交叉验证得到最佳正则超参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最佳正则超参数 alpha 是: 1.0\n"
     ]
    }
   ],
   "source": [
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "#这是为了标出最佳参数的位置，不是必须\n",
    "#plt.plot(np.log10(ridge.alpha_)*np.ones(3), [0.28, 0.29, 0.30])\n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "print ('最佳正则超参数 alpha 是:', ridge.alpha_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.3 Lasso 模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "      <th>coef_lasso</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>yr</td>\n",
       "      <td>4550.708897</td>\n",
       "      <td>1504.623924</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>temp</td>\n",
       "      <td>2654.792827</td>\n",
       "      <td>1778.493414</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>1287.992360</td>\n",
       "      <td>678.352931</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>atemp</td>\n",
       "      <td>995.293778</td>\n",
       "      <td>1546.374034</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>929.887649</td>\n",
       "      <td>84.873020</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>914.410909</td>\n",
       "      <td>914.843092</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>season_4</td>\n",
       "      <td>830.579518</td>\n",
       "      <td>767.205317</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>586.296405</td>\n",
       "      <td>-824.928596</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>517.803038</td>\n",
       "      <td>205.686009</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>409.589079</td>\n",
       "      <td>388.865215</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>407.138803</td>\n",
       "      <td>-725.828529</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>238.417312</td>\n",
       "      <td>227.515740</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>workingday</td>\n",
       "      <td>216.956549</td>\n",
       "      <td>212.558710</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>189.797216</td>\n",
       "      <td>369.663154</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>season_2</td>\n",
       "      <td>85.141889</td>\n",
       "      <td>110.998614</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>77.516263</td>\n",
       "      <td>81.396550</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>66.464787</td>\n",
       "      <td>59.857933</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>43.650546</td>\n",
       "      <td>62.795850</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>5.009200</td>\n",
       "      <td>387.713628</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>instant</td>\n",
       "      <td>-6.919060</td>\n",
       "      <td>1.417157</td>\n",
       "      <td>5.456671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-31.943212</td>\n",
       "      <td>-34.140080</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>season_3</td>\n",
       "      <td>-130.807162</td>\n",
       "      <td>-91.388275</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-191.612446</td>\n",
       "      <td>-191.851510</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-202.493250</td>\n",
       "      <td>-205.574484</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-203.137582</td>\n",
       "      <td>-242.548582</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-263.761415</td>\n",
       "      <td>-248.222941</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-485.714239</td>\n",
       "      <td>106.306513</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-541.439917</td>\n",
       "      <td>298.550050</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>season_1</td>\n",
       "      <td>-784.914245</td>\n",
       "      <td>-786.815656</td>\n",
       "      <td>-341.190505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-1174.845790</td>\n",
       "      <td>-1087.773198</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-1207.111892</td>\n",
       "      <td>-143.125249</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1298.592138</td>\n",
       "      <td>-1142.397276</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>-1323.999988</td>\n",
       "      <td>-1303.708307</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-1486.521042</td>\n",
       "      <td>-194.714350</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns      coef_lr   coef_ridge  coef_lasso\n",
       "33            yr  4550.708897  1504.623924    0.000000\n",
       "27          temp  2654.792827  1778.493414    0.000000\n",
       "13        mnth_9  1287.992360   678.352931    0.000000\n",
       "28         atemp   995.293778  1546.374034    0.000000\n",
       "14       mnth_10   929.887649    84.873020    0.000000\n",
       "17  weathersit_1   914.410909   914.843092    0.000000\n",
       "4       season_4   830.579518   767.205317   -0.000000\n",
       "16       mnth_12   586.296405  -824.928596   -0.000000\n",
       "12        mnth_8   517.803038   205.686009    0.000000\n",
       "18  weathersit_2   409.589079   388.865215   -0.000000\n",
       "15       mnth_11   407.138803  -725.828529   -0.000000\n",
       "26     weekday_6   238.417312   227.515740   -0.000000\n",
       "32    workingday   216.956549   212.558710    0.000000\n",
       "10        mnth_6   189.797216   369.663154    0.000000\n",
       "2       season_2    85.141889   110.998614    0.000000\n",
       "25     weekday_5    77.516263    81.396550    0.000000\n",
       "23     weekday_3    66.464787    59.857933    0.000000\n",
       "24     weekday_4    43.650546    62.795850    0.000000\n",
       "9         mnth_5     5.009200   387.713628    0.000000\n",
       "0        instant    -6.919060     1.417157    5.456671\n",
       "22     weekday_2   -31.943212   -34.140080    0.000000\n",
       "3       season_3  -130.807162   -91.388275    0.000000\n",
       "20     weekday_0  -191.612446  -191.851510   -0.000000\n",
       "21     weekday_1  -202.493250  -205.574484   -0.000000\n",
       "11        mnth_7  -203.137582  -242.548582    0.000000\n",
       "31       holiday  -263.761415  -248.222941   -0.000000\n",
       "8         mnth_4  -485.714239   106.306513    0.000000\n",
       "7         mnth_3  -541.439917   298.550050    0.000000\n",
       "1       season_1  -784.914245  -786.815656 -341.190505\n",
       "30     windspeed -1174.845790 -1087.773198   -0.000000\n",
       "6         mnth_2 -1207.111892  -143.125249   -0.000000\n",
       "29           hum -1298.592138 -1142.397276   -0.000000\n",
       "19  weathersit_3 -1323.999988 -1303.708307   -0.000000\n",
       "5         mnth_1 -1486.521042  -194.714350   -0.000000"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#### Lasso／L1正则\n",
    "# class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, \n",
    "#                                    normalize=False, precompute=’auto’, max_iter=1000, \n",
    "#                                    tol=0.0001, copy_X=True, cv=None, verbose=False, n_jobs=1,\n",
    "#                                    positive=False, random_state=None, selection=’cyclic’)\n",
    "from sklearn.linear_model import LassoCV\n",
    "\n",
    "#设置超参数搜索范围\n",
    "#alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "\n",
    "#生成一个LassoCV实例\n",
    "#lasso = LassoCV(alphas=alphas)  \n",
    "lasso = LassoCV()  \n",
    "\n",
    "#训练（内含CV）\n",
    "lasso.fit(X_train, y_train)  \n",
    "\n",
    "#测试\n",
    "y_test_pred_lasso = lasso.predict(X_test)\n",
    "y_train_pred_lasso = lasso.predict(X_train)\n",
    "\n",
    "# 各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T)), \"coef_lasso\":list((lasso.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3.1 利用评估指标RMSE评估模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The RMSE of LinearRegression on test is 1428.6588490895804\n",
      "The RMSE of LinearRegression on train is 1439.5361015009635\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "# 测试集\n",
    "print('The RMSE of LinearRegression on test is', np.sqrt(metrics.mean_squared_error(y_test, y_test_pred_lasso))) \n",
    "# 训练集\n",
    "print('The RMSE of LinearRegression on train is', np.sqrt(metrics.mean_squared_error(y_train, y_train_pred_lasso))) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3.2 5折交叉验证得到最佳正则超参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最佳正则超参数 alpha 是: 256.4697701374553\n"
     ]
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('最佳正则超参数 alpha 是:', lasso.alpha_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4 三种模型的比较"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![avatar](grid.png)\n",
    "\n",
    "<font size=5 face=\"黑体\">上图为三种模型得到的各个特征系数的比较，我们可以得到岭回归模型相比最小二乘线性回归模型的系数，有所收缩，模型更简单，因为其引入了L2正则；而Lasso模型得到的一部分系数为零，也就是所，该模型更便于选择合适的特征，因为其引入了L1正则。</font>\n",
    "***\n",
    "***\n",
    "\n",
    "![avatar](graph.png)\n",
    "\n",
    "<font size=5 face=\"黑体\">上图为三种模型的RMSE的值的比较，可以得到岭回归的RMSE值在测试集上的误差较小，其性能较好。</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
